4 дня назад
Data Scientist (AI)
150 000 - 200 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Scientist (AI) (LLM-based applications): Building and evaluating agentic AI applications for regulated financial workflows with an accent on LLM evaluation, prompt and context optimization, applied research, and data-driven investment decisions. Focus on designing 0→1 AI systems, benchmarking real-world deployments, exploring emerging agentic techniques, and translating statistical insights for executive audiences.
Location: NYC-Metro; hybrid work
Base compensation: $150,000–$200,000 annually, plus annual bonus and equity.
Company
builds production-ready agentic AI workforces for financial services, running defined workflows within institutional controls and audit boundaries.
What you will do
- Develop methods to evaluate agentic AI system performance and track results over time.
- Optimize prompts and context and apply adapter tuning when appropriate to improve LLM-based applications.
- Design, implement, and validate AI-native systems that combine advanced models, proprietary data, and novel architectures.
- Benchmark systems and support real-world deployment of applied research from initial concept to production.
- Explore emerging AI research, run bold experiments, and identify opportunities for innovation.
- Apply statistics, machine learning, and data science to investment sourcing, screening, due diligence, and asset monitoring.
Requirements
- 5–10 years of experience.
- Deep understanding of designing and evaluating LLM-based applications.
- Experience building intelligent systems with models, including compound AI systems, agentic collaboration, ensembling, ReAct, or graph-of-thoughts techniques.
- Strong programming and data analysis skills.
- Ability to interpret statistical insights for non-technical and executive audiences.
- Regular use of AI tools such as ChatGPT, Cursor, NotebookLM, or Claude Code.
Nice to have
- Experience with financial systems, risk modeling, or decision automation.
- Familiarity with machine learning training and deployment.
- Experience with embedded analytics.
Culture & Benefits
- Work directly with the founders and own key technical decisions from the start.
- Join an early team focused on curiosity, pragmatism, and engineering excellence.
- Annual bonus and equity in addition to base compensation.
- Work on AI systems designed for traceability, inspection, governance, and institutional controls.
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